Abstract

Background

α-Mangostin (α-MG) is a main constituent of the fruit hull of the mangosteen. Previous studies have shown that α-MG has pharmacological activities such as antioxidant, antitumor, anti-inflammatory, antiallergic, antibacterial, antifungal and antiviral effects. This study aims to investigate the anti-inflammatory molecular action of α-MG on gene expression profiles.

Methods

U937 and EL4 cells were treated with different concentrations of α-MG in the presence of 0.1 ng/mL lipopolysaccharide (LPS) for 4 h. The anti-inflammatory effects of α-MG were measured by the levels of tumor necrosis factor (TNF)-α and interleukin (IL)-4 in cell culture media, which were determined with enzyme-linked immunosorbent assay kits. The gene expression profiles of all samples were analyzed with a whole human genome microarray, Illumina BeadChip WG-6 version 3, containing 48804 probes. The protein levels were determined by Western blotting analyses.

Differentiation induction

U937 cells were cultured in RPMI 1640 medium supplemented with 10% (v/v) fetal calf serum, 2 mM glutamine, 100 U/mL penicillin and 100 μg/mL streptomycin at 37°C under 5% CO2. For differentiation induction, the cells were seeded at a density of 2 × l07 cells per T150 flask. Differentiation was initiated by addition of phorbol-12-myristate-13-acetate to the culture medium to a final concentration of 50 ng/mL and allowed to proceed for 24 h. The U937 cells were then washed with complete culture media once and incubated in U937 culture medium for 48 h.

Cytotoxicity assay

Cytotoxicity assays were performed by the MTT method. Cells were incubated with 100 μL of 1 mg/mL MTT for 1 h at 37°C under 5% CO2. DMSO (100 μL) was added to dissolve the crystals and the OD560 was measured with an ELISA reader (Spectrafluor Plus, Tecan, Switzerland). The results were expressed as cell viability percentages among LPS-stimulated cells.

Microarray analysis

RNA isolation

U937 cells were harvested into pellets, washed with PBS and stored at −80°C until extraction. Total RNA and small RNAs from the cultured cells were isolated using the mirVana miRNA Isolation Kit.

Gene expression

The gene expression profiles were analyzed using a whole human genome microarray containing 48,804 probes (BeadChip WG-6 version 3; Illumina Inc., USA). Biotin-labeled complementary RNA (cRNA) for hybridization was generated by in vitro transcription based on the Eberwine protocol using Illumina Human Whole Genome-6 expression BeadChip kits (Illumina Inc, USA). Total RNA (500 ng) was reverse-transcribed into cDNA, followed by linear amplification steps according to an Illumina TotalPrep RNA Amplification Kit (Ambion Inc., USA). Hybridization was performed with 1.5 μg of biotin-labeled cRNA in each BeadChip WG-6 array. After incubation at 58°C for 16 h, the BeadChip WG-6 was washed with fresh wash tray according to Illumina Whohle-Genome Gene Expression Direct Hybridization Assay, stained with streptavidin-Cy3 dye (Amersham Biosciences, Buckinghamshire, UK) and scanned as described in the Illumina manual. The HumanWG-6 v3.0 Expression BeadChip WG-6 contains six arrays on a single BeadChip WG-6, each with 48,804 probes derived from human genes in the NCBI RefSeq and UniGene databases. Each array on the BeadChip WG-6 covers genome-wide transcription of well-characterized genes, gene candidates and splice variants. The intensity of each probe was calculated as the average intensity of at least 15 beads. Array images and data output were processed using Illumina BeadStudio software (Ambion Inc, USA). The analysis methods for the gene expressions using R and BioConductor 2.10 Software Packages (Biobase, beadarray, limma packages of R/BioConductor were used).

Gene expression profiling

The gene expression profiles of undifferentiated and differentiated U937 cells were determined using the Illumina WG-6 version 3 Beadarray (Illumina Inc., USA). The raw intensity of spots was log-2 transformed for subsequent analysis. Quantile normalization was performed within all arrays to adjust the systematic variation of experiments and dye effects. Significantly changed genes were identified by Limma test with BH (Benjamini & Hochberg) adjust P values of less than 0.05.

Pathway and gene ontology analysis

The pathway and gene ontology analyses were performed using the MetaCore software (GeneGo Inc., USA), in which the differentially expressed gene sets for LPS and α-MG comprised the significantly changed genes between the two conditions and were annotated according to their biological processes based on gene ontology information.

Statistical analysis

All experiments were performed in triplicate and repeated independently at least three times. Data were presented as mean ± standard deviation (SD) and analyzed by one-way analysis of variance (ANOVA) using SAS 9.1.3 software (SAS Institute Inc., USA) followed by a Tukey test to determine any significant differences. P values less than 0.05 were considered statistically significant. Dose dependence was visually determined from the dose–response graphs.

Results and discussion

Inhibition of LPS-induced TNF-α and IL-4 production

LPS significantly induced the production of TNF-α and IL-4 in U937 cells. The inhibitory effects of α-MG on inflammatory cytokines were evaluated by measuring the amounts of secreted TNF-α and IL-4 in LPS-stimulated U937 cells after treatment with α-MG. α-MG inhibited the production of TNF-α (P = 0.038) (Figure 1A) and IL-4 (P = 0.04) (Figure 1B) in a dose-dependent manner. The anti-inflammatory effects of α-MG could be attributed to the inhibition of inflammatory cytokine production or a reduction in the number of U937 cells through cytotoxicity. The latter possibility was excluded by comparing the numbers of cells cultured with the different concentrations of α-MG, wherein no significant decreases in cell viability were observed when the concentration was below 15.2 nM (P = 0.1) (Figure 1A). The IC50 of α-MG was 13.4 ± 0.4 nM.

Figure 1

Inhibition of TNF-α and IL-4 secretion from U937 and EL4 cells by α-MG. (A) U937 cells were treated with 0.1 ng/mL LPS in the presence or absence of different concentrations of α-MG, 7.6, 12.5, 30.5 nM, respectively for 4 h. TNF-α secreted into the conditioned media was quantified by ELISA. The TNF-α content (gray bars) and cell viabilities (open bars) are shown. (B) EL4 cells were treated with 0.1 ng/mL LPS in the presence or absence of different concentrations of α-MG, 3.0, 6.1, 12.2 nM, respectively for 18 h. IL-4 secreted into the conditioned media was quantified by ELISA. The IL-4 content (gray bars) and cell viabilities (open bars) are shown. All experiments were performed in triplicate and repeated independently three times. *P < 0.05, significant difference from LPS treatment.

Microarray analysis

Treatment of LPS-stimulated U937 cells with 13.4 nM α-MG changed the gene expression pattern (Figure 2A). There were 1536 and 1491 significantly changed genes at 1 and 6 h with LPS and the combination of LPS and α-MG, respectively. The gene expressions altered after α-MG treatment were involved in pathways related to inflammation-based immune responses, stress responses, regulation of apoptosis and regulation of programmed cell death. Among the approximately 183 genes showing the strongest suppression, 46 genes were related to immune responses and inflammatory responses (Figure 2B). These immune response-related pathways were involved in IL-1 signaling, oncostatin M (OSM) signaling, cytokine production, and Th1 and Th2 cell differentiation.

OSM is expressed in autoimmune diseases, including rheumatoid arthritis, multiple sclerosis and inflammatory conditions [11]. We observed that α-MG is a promising agent for autoimmune diseases (unpublished data). The results from the microarray showed that JUNB, c-Jun, OSM and STAT1 were differentially expressed between the LPS and α-MG-cotreated and LPS-treated cells in the OSM pathway (Figure 3). α-MG may regulate OSM signaling via MAPK pathways and related downstream proteins, including STAT1, c-Jun and c-Fos. The inhibitory actions on three MAPK pathways, ERK1/2, JNK and p38, were examined to delineate the effects of α-MG.

Decrease in LPS-mediated MAPK activation

LPS treatment induced the phosphorylation of p38, ERK1/2 and JNK, and α-MG treatment attenuated these responses in a dose-dependent manner (P = 0.008 for phospho-p38; P = 0.016 for phospho-ERK1/2; P = 0.01 for phospho-JNK) (Figure 4). The level of p38 phosphorylation was significantly decreased compare with ERK1/2 and JNK (Figure 4). α-MG (12 nM) greatly inhibited p38 phosphorylation, and the phosphorylation was reduced to just 38% of that in LPS-treated cells.

Figure 4

α-MG decreases LPS-mediated activation of MAPK pathways in U937 cells. U937 cells were treated with α-MG in the presence of 0.1 ng/mL LPS for 4 h and then lysed. The cell lysates were subjected to Western blotting analyses with ERK1/2, JNK, and p38. Western blots with anti-phospho-ERK1/2, anti-phospho-JNK, and anti-phospho-p38. β-tubulin was evaluated as a loading control, and the protein expression levels were normalized by the corresponding β-tubulin expression levels. Data are expressed as fold phosphorylation normalized to LPS (12 nM α-MG, closed bars; 6 nM α-MG, open bars). All experiments were performed in triplicate and repeated independently three times. *P < 0.05, significant difference from LPS treatment.

EIK-1, MMK3/MMK6 and MAPKAPK-2 are substrates of p38 [12], and the effects of α-MG on their phosphorylation were also examined. LPS treatment induced phosphorylation of EIK-1 and MMK3/MMK6, and α-MG treatment attenuated these responses in a concentration-dependent manner (P = 0.038 for phospho-EIK-1; P = 0.0441 for phospho-MMK3/MMK6; P = 0.0453 for phospho- MAPKAPK-2). EIK-1, MMK3/MMK6 and MAPKAPK-2 phosphorylation was greatly inhibited by 12 nM α-MG, and the phosphorylation was reduced to just 78–82% of that in LPS-treated cells (Figure 5). These findings suggest that α-MG exhibits anti-inflammatory activity by inhibiting MAPK phosphorylation, especially in the p38 pathway including EIK-1, MMK3/MMK6 and MAPKAPK-2.

Figure 5

α-MG decreases LPS-mediated p38 MAPK activation. U937 cells were treated with α-MG in the presence of 0.1 ng/mL LPS for 4 h and then lysed. The cell lysates were subjected to Western blotting analysis with ELK-1, MMK3/MMK6, and MAPKAPK-2. Western blots with anti-phospho- ELK-1, anti-phospho- MMK3/MMK6, and anti-phospho- MAPKAPK-2. β-tubulin was evaluated as a loading control, and the protein expression levels were normalized by the corresponding β-tubulin expression levels. Data are expressed as fold phosphorylation normalized to LPS (12 nM α-MG, closed bars; 6 nM α-MG, open bars). All experiments were performed in triplicate and repeated independently three times. *P < 0.05, significant difference from LPS treatment.

Regulation of STAT1, c-Jun and c-Fos

The results from the microarray showed that JUNB, c-Jun, OSM and STAT1 were differentially expressed between the LPS and α-MG-cotreated and LPS-treated cells in the OSM pathway. The protein levels of STAT1, c-Jun and c-Fos were determined by Western blotting analyses. Specifically, α-MG pretreatment attenuated LPS-induced phosphorylation of c-Jun and c-Fos and downstream targets of JNK and ERK1/2 (P = 0.04 for phospho-c-Fos) (Figure 6). We demonstrated that α-MG reduced the induction of STAT1 (P = 0.0012), c-Jun and c-Fos in a concentration-dependent manner.

Figure 6

α-MG regulates STAT 1, c-Jun and c-Fos. U937 cells were treated with α-MG in the presence of 0.1 ng/mL LPS for 4 h and then lysed. The cell lysates were subjected to Western blotting analyses with STAT 1, c-Jun, c-Fos. Western blots with anti-phospho- STAT 1, anti-phospho- c-Jun, and anti-phospho- c-Fos. β-tubulin was evaluated as a loading control, and the protein expression levels were normalized by the corresponding β-tubulin expression levels. Data are expressed as fold phosphorylation normalized to LPS (12 nM α-MG, closed bars; 6 nM α-MG, open bars). All experiments were performed in triplicate and repeated independently three times. *P < 0.05, significant difference from LPS treatment.

As shown in Figure 7, we have demonstrated that the anti-inflammatory effects of α-MG involves the following: (1) attenuation of LPS-induced production of IL-4 and TNF-α; (2) attenuation of LPS-induced activation of JNK, ERK1/2 and p38; (3) reduction of LPS-induced activation of EIK-1, MMK3/MMK6 and MAPKAPK-2; and (4) attenuation of LPS-mediated suppression of STAT1, c-Jun and c-Fos expression. Taken together, these new findings demonstrate that α-MG inhibits LPS-mediated activation of inflammatory AP-1, MAPK and MAPK-related proteins, including STAT1, c-Jun and c-Fos.

Figure 7

Pathway analysis of α-MG effects on gene expression in U937 cells.

Conclusion

This study has demonstrated that α-MG attenuates LPS activation of MAPK, STAT1, c-Fos, c-Jun and EIK-1, thereby inhibiting TNF-α and IL-4 production in U937 cells.

Abbreviations

PMA:

Phorbol-12-myristate-13-acetate

IC50:

Half maximal inhibitory concentration

MTT:

3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2 H-tetrazolium bromide

PBS:

Phosphate-buffered saline

ANOVA:

Analysis of variance

AP-1:

Activator protein 1

JNK:

c-Jun N-terminal kinase

MAPKAPK-2:

Mitogen activated protein kinase-activated protein kinase-2

cDNA:

Complementary DNA

cRNA:

Complementary RNA

ELISA:

Enzyme-linked immunosorbent assay

Elk-1:

Ets-like molecule 1

ERK1/2:

Extracellular signal-regulated kinases 1 and 2

IKK:

IκB kinase

IL:

Interleukin

iNOS:

Inducible NOS

LPS:

Lipopolysaccharide

MMK3:

MAPK kinase 3

MMK6:

MAPK kinase 6

MAPK:

Mitogen-activated protein kinase

NF-κB:

Nuclear factor-κB

OSM:

Oncostatin M

PGE2:

Prostaglandin E2

STAT1:

Signal transducers and activators of transcription-1.

Declarations

Acknowledgements

The study was financially supported by grants from the Industrial Technology Research Institute (ITRI) (Grant Number A356EJ2100) and Gifu Pharmaceutical University.

Authors' original submitted files for images

Below are the links to the authors’ original submitted files for images.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

LTL and IM designed the study. SHL performed the Western blotting and statistical analyses, and wrote the manuscript. NYH, KKH and YCS performed the cytokines assay experiments. JML, TYC, WHW and TSC performed the microarray experiments and wrote the manuscript. All authors read and approved the final manuscript.

Copyright

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.